IEEE Sensors Journal最新文献

{"title":"Downhole Microseismic Detection Using Fiber-Optic Distributed Acoustic Sensing Based on Segmentation Model and Connected Domain Algorithm","authors":"Xike Yang;Honghui Wang;Xiang Wang;Tong Liu;Wei Wu;Qianfeng Shui;Jizhou Ren","doi":"10.1109/JSEN.2025.3553263","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3553263","url":null,"abstract":"The widespread adoption of fiber-optic distributed acoustic sensing (DAS) technology in oil and gas production, the timely and precise identification of microseismic events within DAS datasets holds importance for enhancing both the efficacy and safety of mining operations. The current DAS microseismic detection methods, including template-matching technology and convolutional neural network (CNN)-based approaches, predominantly face challenges such as high computational complexity, slow detection speed, and low detection accuracy. In response, we introduce the SegDetection deep learning model, a semantic segmentation model that integrates dynamic snake convolution with MobileNetV3 to enhance feature extraction capabilities. The model employs lite reduced atrous spatial pyramid pooling (LRASPP) as its segmentation head network. Subsequently, a two-stage connected domain algorithm is utilized to produce prediction boxes and confidence scores. To enhance the segmentation accuracy of our model, we implement a segmentation correction strategy. In the microseismic detection task using the downhole DAS microseismic dataset in Utah, USA, our proposed method achieved an F1-score of 0.902. After applying the error segmentation correction strategy, the F1-score improved to 0.951. The experimental results indicate that the method proposed in this article exhibits commendable performance in downhole DAS microseismic detection. In addition, the error segmentation and correction strategy introduced significantly enhances the model’s detection accuracy, suggesting its broad applicability to various downhole DAS microseismic detection tasks.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15116-15129"},"PeriodicalIF":4.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Soil Moisture Sensing System Powered by Self-Harvesting Soil Energy","authors":"Zenan Hu;Yizhou Qi;Shengyao Jia;Yanwei Sun;Qing Li;Ge Shi","doi":"10.1109/JSEN.2025.3551324","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3551324","url":null,"abstract":"To address the growing demand for self-sustaining sensing systems powered by renewable energy for environmental monitoring, this article proposes a double-helical structure soil energy harvesting device and an integrated system for soil energy harvesting and moisture content sensing detection. The integrated system includes dc-dc converters, microcontrollers, and energy storage. The prepared double-helix soil battery (zinc-copper electrode) can provide a maximum output power of 0.2 mW under a 1-k<inline-formula> <tex-math>$Omega $ </tex-math></inline-formula> load. This device increases power generation by reducing the distance between electrodes and increasing the contact area between electrodes. While harvesting direct current from the soil, the system can simultaneously monitor soil moisture content, using the relationship between electrical energy and soil moisture content to achieve integrated energy and information management. The system can achieve a measurement error of less than 2% for soil moisture content in the range of 5%–35%. This technology enables self-powered soil moisture monitoring and has promising applications in smart agriculture for soil condition monitoring and in landslide soil environment monitoring. Additionally, it can provide auxiliary power for field environmental monitoring equipment and sensors in areas with limited power supply.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15356-15366"},"PeriodicalIF":4.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"sEMG-Based Knee Angle Prediction: An Efficient Framework With XGBoost Feature Selection and Multiattention LSTM","authors":"Liuyi Ling;Liyu Wei;Bin Feng;Zhipeng Yu;Long Wang","doi":"10.1109/JSEN.2025.3553533","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3553533","url":null,"abstract":"Accurate prediction of lower limb joint angles is essential for enabling natural human-exoskeleton interaction in rehabilitation robotics. This study proposes a novel framework for knee joint angle prediction using surface electromyography (sEMG) signals, integrating an XGBoost-driven feature selection algorithm and a multiattention hybrid-enhanced long short-term memory (LSTM) network. First, sEMG signals were acquired from healthy participants during dynamic lower limb movements. After preprocessing, temporal and spectral features were extracted, after which the eXtreme Gradient Boosting (XGBoost) algorithm was applied to eliminate redundant features, reducing input dimensionality while maintaining predictive accuracy. Finally, the reduced features were fed into the proposed model, which leverages hybrid attention mechanisms to enhance temporal dependencies and feature relevance. The experimental results validate that the XGBoost-driven feature selection framework significantly minimizes redundancy in sEMG feature extraction. When evaluating the performance of joint angle prediction, the mean absolute error (MAE), root mean square error (RMSE), adjusted <inline-formula> <tex-math>${R}^{{2}}$ </tex-math></inline-formula>, and Pearson correlation coefficient (CC) of the proposed model were 2.47°, 3.55°, 0.95, and 0.98, outperforming traditional machine learning (ML) algorithms and the benchmarks CNN, LSTM, TCN, and CNN-BiLSTM. The framework’s superior computational efficiency and prediction accuracy highlight its potential for real-time implementation in exoskeleton systems, addressing critical limitations in existing control paradigms. This advancement paves the way for adaptive human-robot collaboration in clinical rehabilitation settings.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"16501-16514"},"PeriodicalIF":4.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pixel-Level Multidirectional Image Sharpness Linear Assessment for Optical Image Stabilizer Performance Monitoring","authors":"Yuhang Zhou;Zhe Zhang;Bokang Yang;Jie Ma","doi":"10.1109/JSEN.2025.3553532","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3553532","url":null,"abstract":"Linear quantification of blur intensity in different directions of an image and blur-type classification are crucial for the detection of anomalies and optimization calibration of widely used optical image stabilizer (OIS). However, previous image quality assessment methods mainly focused on isotropic blur, emphasizing the correlation with subjective ratings, making it difficult to provide multidirectional linear sharpness assessment. Moreover, they invariably offer a single evaluation score regardless of the kind of fuzziness. In this article, we propose a pixel-level multidirectional image sharpness (PMIS) linear assessment method that, to our knowledge, is the first to provide the capability to linearly quantify blur across multiple directions and distinguish blur types in an end-to-end manner while assessing the degree of image blur. We introduce a novel method for extracting edge information to characterize image blur, significantly enhancing correlation with the human visual system (HVS) in blur perception by filtering out high-frequency edge noise. Uniform edge block selection and data postprocessing are introduced to adapt to HVS characteristics and enhance robustness. Using blur results from four different directions and simply setting thresholds, we are able to achieve an 84.5% classification accuracy in distinguishing between defocus blur, motion blur, and clear images. In addition, we creatively make a motion blur image quality (MBIQ) database, accurately representing motion blur through the concrete physical quantity of rotational speed. Experimental results confirm that PMIS achieves significant improvements over the previous methods especially on databases with anisotropic motion blur.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15204-15215"},"PeriodicalIF":4.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel Planar Waveguide-Coupled D-Shaped Optical Fiber Sensor to Generate Fano Resonance for Enhanced Refractive Index Sensing Applications","authors":"Rajiv Maurya;Ankit Mishra;Chandan Singh Yadav;Abhishek Upadhyay;Gaurav Sharma;Vivek Singh","doi":"10.1109/JSEN.2025.3552984","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3552984","url":null,"abstract":"In this article, the generation of Fano resonance (FR) in a novel optical fiber platform, which addresses a significant challenge within the scientific community, is theoretically investigated. The proposed sensor is designed with a D-shaped surface plasmon resonance (SPR) fiber coupled with a three-layer planar waveguide (PWG) structure for inline and enhanced refractive index (RI) sensing applications. Our analysis demonstrates that an optimum thickness of low index dielectric material, i.e., cytop fluoropolymer, as a coupling layer is required to generate FR in association with SPR. It is observed that the FR demonstrates a significant enhancement in the figure of merit (FOM), achieving 6383 RIU^-1 for wavelength interrogation and 13 195 a.u./RIU for intensity interrogation at <inline-formula> <tex-math>${d} _{f} ,, =520$ </tex-math></inline-formula> nm and <inline-formula> <tex-math>${d} _{c} ,, =700$ </tex-math></inline-formula> nm. These values greatly surpass the FOM of conventional SPR-based sensors, which are 34.90 RIU^-1 and 39.96 a.u./RIU. Also, the FOM increases by increasing the thickness of coupling layer. Furthermore, FWHM of the FR is consistent with the length of D-shaped region, whereas FWHM of SPR increases as the length of D-shaped region increases. The penetration depth of FR mode’s evanescent field in the sensing region also increases with the film layer thickness, consistently exceeding the penetration depth of SPR (122.47 nm). Hence, the FR mode is proposed as the sensing signal instead of conventional SPR mode because it offers superior performance compared in terms of FOM and penetration depth.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15109-15115"},"PeriodicalIF":4.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, Simulation, and Characterization of a Novel Optical-Piezoelectric Micromechanical Ultrasonic Transducer (OpMUT)","authors":"Jia-Ling Lin;Shao-Wei Wu;Ju-Fong Chiu;Ya-Han Liu;Chih-Hsien Huang","doi":"10.1109/JSEN.2025.3553480","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3553480","url":null,"abstract":"In this study, we use piezoelectric materials to overcome the high impedance and electromagnetic interference susceptibility of piezoelectric micromachined ultrasonic transducers (pMUTs). We demonstrate the design and simulation of a novel optical-pMUT (OpMUT) that integrates a photonic ring resonator into the traditional pMUT. When the OpMUT receives ultrasound waves, its diaphragm vibrates, and the length of the ring waveguide changes. Consequently, the ring waveguide’s coupling wavelength will shift, and the variation of the bus waveguide’s output light intensity can represent the acoustic signals. This study uses the finite element method (FEM) and numerical analysis to optimize the optical ring resonator’s width, radius, and placement. We compare the signal-to-noise ratio (SNR) and noise-equivalent pressure (NEP) of the proposed OpMUT with those of the state-of-the-art pMUT, which has an SNR of 37.3 dB at 1 Pa and an NEP of 0.0014 Pa. When the radii of the ring waveguides are 10.63, 21.27, and <inline-formula> <tex-math>$35.45~mu $ </tex-math></inline-formula>m, the SNR values of the 150-kHz OpMUTs are 50.8, 67.2, and 72.6 dB at 1 Pa, whereas the NEPs are 0.00174, 0.00067, and 0.00029 Pa. Hence, the proposed OpMUT is considerably better than its competitor. Future improvements in the sensing capability of the micromachined ultrasonic transducers are expected.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15194-15203"},"PeriodicalIF":4.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facial Remote Photoplethysmography for Continuous Heart Rate, Stroke Volume, and Systemic Vascular Resistance Monitoring During Prolonged Warm/Cold Fluid Bolus Administration","authors":"Mahdi Momeni;Sophie Wuthe;Michaela Bitten Mølmer;Emilie Löbner Svendsen;Mikkel Brabrand;Peter Biesenbach;Daniel Teichmann","doi":"10.1109/JSEN.2025.3553368","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3553368","url":null,"abstract":"Hemodynamic parameters—stroke volume (SV), systemic vascular resistance (SVR), and heart rate (HR)—are critical for clinical monitoring, particularly in emergency and critical care settings. This study evaluates the feasibility of a noninvasive, noncontact monitoring approach using imaging photoplethysmography (iPPG), which applies camera-based PPG and a signal processing pipeline implemented in MATLAB. A total of 25 prolonged video recordings (2500 min) were collected from 16 healthy volunteers at Odense University Hospital, while they received intravenous infusions of warm (<inline-formula> <tex-math>$37~^{circ }$ </tex-math></inline-formula>C) and cold (<inline-formula> <tex-math>$15~^{circ }$ </tex-math></inline-formula>C) Ringer’s lactate. To ensure data reliability, video quality and head motion were systematically analyzed. HR estimation using the plane-orthogonal-to-skin (POS) method achieved an average absolute error (avAE) of 4.28 bpm, with the best accuracy of 2.18 bpm, while the CHROM method yielded similar performance (4.27-bpm average error and 2.55-bpm best accuracy). SV and SVR demonstrated moderate correlation with reference measures (<inline-formula> <tex-math>${r} = {0.571}$ </tex-math></inline-formula> and <inline-formula> <tex-math>${r} = {0.596}$ </tex-math></inline-formula>, respectively) across five regions of interest. The best correlations for SV and SVR were <inline-formula> <tex-math>${r} = {0.846}$ </tex-math></inline-formula> and <inline-formula> <tex-math>${r} = {0.873}$ </tex-math></inline-formula>, respectively, indicating strong potential for accurate noncontact monitoring. These results suggest that iPPG can provide real-time cardiovascular insights during fluid therapy, with potential applications in telemedicine and mobile health. However, to robustly generalize the findings of this study, limitations such as interindividual variability and the need to include diverse patient populations should be considered. This study provides the first demonstration of iPPG feasibility for prolonged emergency fluid administration, paving the way for further research in dynamic clinical environments.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"16151-16169"},"PeriodicalIF":4.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing Mode-Division Multiplexing for Multicell Trapping","authors":"Bingjie Bi;Cun Zhao;Chunlei Jiang;Penghui Dai;Hongda Jiang;Peng Chen;Xiufang Wang;Yu Sun;Xu Liu","doi":"10.1109/JSEN.2025.3553389","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3553389","url":null,"abstract":"We propose a novel single-fiber optical tweezers technology based on mode-division multiplexing (MDM) using LP₀₁, LP₁₁, and LP₂₁ modes. This method enables effective coupling between multimode fibers (MMFs) and single-mode fibers (SMFs) through precise coaxial splicing. By exciting multiple modes in the MMF and employing the SMF for mode filtering, we selectively retain the LP₀₁, LP₁₁, and LP₂₁ modes while effectively suppressing higher order modes. Additionally, we have designed and fabricated an abruptly tapered fiber (ATF) probe to converge the beams of different modes, generating distinct focused light fields at the probe’s tip and sides. The simulation and experimental results indicate that this technology can establish multiple stable optical traps, allowing for the effective trapping of several cells. This approach provides precise manipulation tools for studying interactions, such as collective sensing and metabolic cooperation among cells, demonstrating significant application potential, particularly in single-cell analysis, multicellular assembly, and biological micromanipulation.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15130-15135"},"PeriodicalIF":4.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ML-Aided 2-D Indoor Positioning Using Energy Harvesters and Optical Detectors for Self-Powered Light-Based IoT Sensors","authors":"Amila Perera;Khojiakbar Botirov;Hazem Sallouha;Marcos Katz","doi":"10.1109/JSEN.2025.3552905","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3552905","url":null,"abstract":"Advancements in 6G and IoT sensor networks prioritize sustainability and energy efficiency, with positioning services essential for improved functionality. Light-based IoT (LIoT) systems present a promising solution by achieving energy autonomy through photovoltaic (PV) energy harvesting (EH) and enabling visible light communication (VLC) via indoor luminaries as optical access points (OAPs). This research explores the repurposing of energy harvesters at LIoT nodes and detectors at OAPs for positioning and orientation detection in energy-autonomous, battery-free, intermittently operating LIoT sensor networks. We propose potential node and OAP designs, validated by proof-of-concept prototypes, utilizing conventional machine learning (ML) and deep neural networks (DNNs) to enhance localization. Performance evaluations demonstrate 80% positioning accuracy within 12.5-cm tolerance and 68% orientation prediction accuracy. This approach allows LIoT devices to communicate, harvest energy, and determine their position and orientation using the same illumination from OAPs, underscoring the potential of this LIoT-based system as a sustainable solution for next-generation IoT sensors.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"15958-15967"},"PeriodicalIF":4.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10944259","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensor-Based Performance Analysis and Intelligent Fault Diagnosis of Pneumatic-Hydraulic Actuated Valves","authors":"Shijian Zhang;Xuezhong Chen;Min Luo;Jingdong Chen;Hong Yang;Bo He;Huai Yang;Yibing Zhang;Xubing Liu;Xuan Zhou;Zhihuan Wang;Liang Chen;Jingyun Liang;Zhenglong Ai;Min Qin;Yi Qin","doi":"10.1109/JSEN.2025.3552261","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3552261","url":null,"abstract":"Pneumatic-hydraulic actuated ball valves are critical components in pipeline rupture protection and emergency shutdown systems for large-diameter natural gas transmission pipelines. Traditional maintenance methods, relying on periodic inspections and reactive maintenance, often result in delayed fault detection, which increases safety risks. In order to address this challenge, this study proposes an innovative intelligent fault diagnosis approach that significantly enhances early fault detection and predictive maintenance without requiring structural modifications to the valve. The main contributions of this work are: 1) the development of a novel time-frequency analysis-based feature extraction method for current and pressure signals, which improves fault signature reliability and distinguishes fault patterns more effectively; and 2) the application of long short-term memory (LSTM) networks optimized using an improved particle swarm optimization (IPSO) algorithm, achieving 100% diagnostic accuracy for both solenoid valve and mechanical faults. Experimental results demonstrate the superiority of the proposed approach, with field tests successfully detecting torque anomalies and identifying risks related to solenoid valve power-off logic. This approach provides a robust solution for transitioning from preventive to predictive maintenance, significantly improving operational safety and pipeline reliability.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 9","pages":"16124-16139"},"PeriodicalIF":4.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}